Summary
The M-Group at KU Leuven Bruges Campus is looking for a highly motivated candidate for a PhD position focused on leveraging Causal Machine Learning techniques for root cause analysis in multimodal industrial data. This interdisciplinary research opportunity aims to enhance understanding of complex industrial failure mechanisms through innovative AI methods.
PhD Position on Causal Machine Learning for Industrial Root Cause Analysis, KU Leuven, Bruges Campus, Belgium
Designation
PhD Researcher
Research Area
Causal Machine Learning, Industrial Systems, Root Cause Analysis, Data Science
Location
KU Leuven, Bruges Campus, Belgium
Eligibility/Qualification
- Master’s degree in Computer Science, Artificial Intelligence, Electrical Engineering, Mathematical Engineering or related field.
- Above-average academic performance compared to peers.
- Proficiency in written and spoken English.
- Experience in machine/deep learning; familiarity with causal machine learning and time-series analysis is a plus.
- Proficient in Python and data science/machine learning toolkits.
Job Description
- Research Focus: Develop hybrid causal discovery methods from heterogeneous industrial data, including multivariate time-series sensor data and engineering models.
- Tasks Include:
- Designing algorithms to extract causal graphs that identify dependencies driving failures.
- Implementing online updating strategies for causal graphs.
- Estimating effect sizes of root causes using machine learning techniques.
- Collaborating closely with industrial partners and validating methods on real-world datasets.
How to Apply
Interested candidates should submit the following documents as a single PDF via the online application tool:
- Motivation Letter
- Complete Academic CV
- List of Publications (if applicable)
- Copies of Diplomas
- Transcript of Records
- English Summary of Master Thesis
- Proof of English Language Proficiency (if available)
- Reference Letter or Contact Information for a Reference
Last Date for Apply
June 18, 2026 – 23:59 CET
This is an outstanding opportunity to engage in cutting-edge research within a collaborative environment while contributing to significant advances in industrial applications of AI.
